Posts filed under “Data Analysis”

BLS Margin of Error

Sy Harding, author of Riding the Bear, writes:  “In the fine print of the employment report each month, under a section titled ‘Reliability of the Estimates’, is this statement: ‘The confidence level for the  monthly change in total employment is on the order of plus or minus 430,000 jobs.’

Given our recent lament about the precision of the monthly NFP data, even we found that hard to believe. So I went to the most recent release, and scanned:

What do you know! There is was in BLS print:

Reliability of the estimates

Statistics based on the household and establishment surveys are subject to both sampling and nonsampling error.  When a sample rather than the entire population is surveyed, there is a chance that the sample estimates may differ from the "true" population values they represent.  The exact difference, or sampling error, varies depending on the particular sample selected, and this variability is measured by the standard error of the estimate.  There is about a 90-percent chance, or level of confidence, that an estimate based on a sample will differ by no more than 1.6 standard errors from the "true" population value because of sampling error. BLS analyses are generally conducted at the 90-percent level of confidence.

For example, the confidence interval for the monthly change in total employment from the household survey is on the order of plus or minus 430,000.  Suppose the estimate of total employment increases by 100,000 from one month to the next.  The 90-percent confidence interval on the monthly change would range from -330,000 to 530,000 (100,000 +/- 430,000).

These figures do not mean that the sample results are off by these magnitudes, but rather that there is about a 90-percent chance that the "true" over-the-month change lies within this interval. Since this range includes values of less than zero, we could not say with confidence that employment had, in fact, increased. If, however, the reported employment rise was half a million, then all of the values within the 90-percent confidence interval would be greater than zero.  In this case, it is likely (at least a 90-percent chance) that an employment rise had, in fact, occurred. At an unemployment rate of around 5.5 percent, the 90-percent confidence interval for the monthly change in unemployment is about +/- 280,000, and for the monthly change in the unemployment rate it is about +/- .19 percentage point.

Yes, its true: Zero was within the 90% confidence interval for the monthly change for nearly every month for the past 2 years!

Harding states this is nearly double the prior fudge factor.

Source:
Employment Situation: OCTOBER 2006
BLS, Friday, November 3, 2006.
http://www.bls.gov/news.release/pdf/empsit.pdf

Download Employment Situation.pdf

Category: Data Analysis, Economy, Employment

US Treasury Dept Usurping Fed, Fueling Markets

Category: Data Analysis, Politics

Fed Official Says Bad Data Helped Fuel Rate Cuts, Housing Speculation

Category: Data Analysis, Economy, Federal Reserve, Inflation

Analyzing why “It’s a great time to buy or sell a home!”

Yesterday, we discussed the $40M NAR ad campaign, “It’s a great time to buy or sell a home!” On the way home, I actually saw the full page ad in the Personal section of the WSJ; (Unfortunately for the NAR, the section’s front page article was “The New Word in Home Sales: ‘Canceled’) I read…Read More

Category: Data Analysis, Economy, Psychology, Real Estate

NFP: Retiring the Over/Under Bet

Category: Data Analysis, Employment

Actual GDP: ~0%

Category: Data Analysis, Economy

Middle Class Squeeze Continues

Category: Data Analysis, Economy, Employment, Psychology

A Closer Look at New Home Sales Data

Yesterday’s increase in New Home Sales caught some economists by surprise. I look at those sorts of numbers suspiciously. Any time I want some insight into any particular datapoint, I find it instructive to go to the actual government source’s website, and simply click around. If you do this with a skeptical eye, you may…Read More

Category: Data Analysis, Economy, Real Estate

Our piddlingly tiny Defense Budget

Category: Data Analysis, War/Defense

Delving Deeper Into Housing

Category: Data Analysis, Real Estate